Showing 1 - 20 results of 32 for search '(( complement 5a algorithm ) OR ((( second multi algorithm ) OR ( neural scheduling algorithm ))))', query time: 0.13s Refine Results
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    A Parallel Neural Networks Algorithm for the Clique Partitioning Problem by Harmanani, Haidar M.

    Published 2002
    “…The clique partitioning problem has important applications in many areas including VLSI design automation, scheduling, and resources allocation. In this paper we present a parallel algorithm to solve the above problem for arbitrary graphs using a Hopfield Neural Network model of computation. …”
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    article
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    A Neural Networks Algorithm for the Minimum Colouring Problem Using FPGAs† by Harmanani, Haidar

    Published 2010
    “…The proposed algorithm has a time complexity of O(1) for a neural network with n vertices and k colours. …”
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    article
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    Optimum sensors allocation for drones multi-target tracking under complex environment using improved prairie dog optimization by Abu Zitar, Raed

    Published 2024
    “…This paper presents a novel hybrid optimization method to solve the resource allocation problem for multi-target multi-sensor tracking of drones. This hybrid approach, the Improved Prairie Dog Optimization Algorithm (IPDOA) with the Genetic Algorithm (GA), utilizes the strengths of both algorithms to improve the overall optimization performance. …”
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    Deep Reinforcement Learning for Resource Constrained HLS Scheduling by Makhoul, Rim

    Published 2022
    “…The two main steps in HLS are: operations scheduling and data-path allocation. In this work, we present a resource constrained scheduling approach that minimizes latency and subject to resource constraints using a deep Q learning algorithm. …”
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    masterThesis
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    Fixed set search applied to the multi-objective minimum weighted vertex cover problem by Raka Jovanovic (17947838)

    Published 2022
    “…One important characteristic of the proposed GRASP is that it avoids the use of weighted sums of objective functions in the local search and the greedy algorithm. In the second stage, the bi-objective GRASP is extended to the FSS by adding a learning mechanism adapted to multi-objective problems. …”
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    Multi-class subarachnoid hemorrhage severity prediction: addressing challenges in predicting rare outcomes by Muhammad Mohsin Khan (22150360)

    Published 2025
    “…Feature selection was done using a Random Forest algorithm to identify the top 20 features for the SAH severity prediction. …”
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    Privacy-preserving energy optimization via multi-stage federated learning for micro-moment recommendations by Md Mosarrof Hossen (21399056)

    Published 2025
    “…A comparative evaluation of three FL algorithms (FedAvg, FedProx, Mime-lite) identifies the most suitable aggregation strategy. …”
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    Prediction of EV Charging Behavior Using Machine Learning by Shahriar, Sakib

    Published 2021
    “…Using data-driven tools and machine learning algorithms to learn the EV charging behavior can improve scheduling algorithms. …”
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    article
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    YOLO-DefXpert: An Advanced Defect Detection on PCB Surfaces Using Improved YOLOv11 Algorithm by Prabu Selvam (22330264)

    Published 2025
    “…Second, the standard convolutional operations are replaced with Deformable Convolutional Networksv2 (DCNv2) in the neck section to improve robustness in identifying multi-scale defects. …”
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    Defense against adversarial attacks: robust and efficient compressed optimized neural networks by Insaf Kraidia (19198012)

    Published 2024
    “…First, introducing a pioneering batch-cumulative approach, the exponential particle swarm optimization (ExPSO) algorithm was developed for meticulous parameter fine-tuning within each batch. …”
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    Stability improvement of the PSS-connected power system network with ensemble machine learning tool by M.S. Shahriar (19517536)

    Published 2022
    “…The backtracking search algorithm (BSA) based proposed ensemble model is formed by combining three machine learning (ML) techniques, namely the extreme learning machine (ELM), neurogenetic (NG) system, and multi-gene genetic programming (MGGP). …”
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